Reducing context models for entropy coding of transform coefficients

ABSTRACT

A method of video decoding in a decoder is provided. In the method, a coded video bitstream is received. For a scan position in the transform block, an offset value is determined based on a template magnitude for a template of the scan position. The offset value is constrained based on a first number of context models for each frequency region. For the scan position, a base value is determined based on the first number and the scan position. A context model index is determined based on a sum of the offset value and the base value. A context model is selected from a plurality of context models based on the context model index. A value of a syntax element at the scan position is determined based on the context model. A transform coefficient at the scan position is determined based on the value of the syntax element.

INCORPORATION BY REFERENCE

This application is a continuation of U.S. application Ser. No.17/450,013, filed on Oct. 5, 2021, which claims priority to U.S. patentapplication Ser. No. 16/904,000, now U.S. Pat. No. 11,212,555, filed onJun. 17, 2020, which claims the benefit of priority to U.S. ProvisionalApplication No. 62/863,742, “METHOD OF REDUCING CONTEXT MODELS FORENTROPY CODING OF TRANSFORM COEFFICIENT SIGNIFICANT FLAG” filed on Jun.19, 2019. The entire disclosures of the prior applications are herebyincorporated by reference.

TECHNICAL FIELD

The present disclosure describes embodiments generally related to videocoding.

BACKGROUND

The background description provided herein is for the purpose ofgenerally presenting the context of the disclosure. Work of thepresently named inventors, to the extent the work is described in thisbackground section, as well as aspects of the description that may nototherwise qualify as prior art at the time of filing, are neitherexpressly nor impliedly admitted as prior art against the presentdisclosure.

Video coding and decoding can be performed using inter-pictureprediction with motion compensation. Uncompressed digital video caninclude a series of pictures, each picture having a spatial dimensionof, for example, 1920×1080 luminance samples and associated chrominancesamples. The series of pictures can have a fixed or variable picturerate (informally also known as frame rate), of, for example 60 picturesper second or 60 Hz. Uncompressed video has significant bitraterequirements. For example, 1080p60 4:2:0 video at 8 bit per sample(1920×1080 luminance sample resolution at 60 Hz frame rate) requiresclose to 1.5 Gbit/s bandwidth. An hour of such video requires more than600 GBytes of storage space.

One purpose of video coding and decoding can be the reduction ofredundancy in the input video signal, through compression. Compressioncan help reduce the aforementioned bandwidth or storage spacerequirements, in some cases by two orders of magnitude or more. Bothlossless and lossy compression, as well as a combination thereof can beemployed. Lossless compression refers to techniques where an exact copyof the original signal can be reconstructed from the compressed originalsignal. When using lossy compression, the reconstructed signal may notbe identical to the original signal, but the distortion between originaland reconstructed signals is small enough to make the reconstructedsignal useful for the intended application. In the case of video, lossycompression is widely employed. The amount of distortion tolerateddepends on the application; for example, users of certain consumerstreaming applications may tolerate higher distortion than users oftelevision distribution applications. The compression ratio achievablecan reflect that: higher allowable/tolerable distortion can yield highercompression ratios.

A video encoder and decoder can utilize techniques from several broadcategories, including, for example, motion compensation, transform,quantization, and entropy coding.

Video codec technologies can include techniques known as intra coding.In intra coding, sample values are represented without reference tosamples or other data from previously reconstructed reference pictures.In some video codecs, the picture is spatially subdivided into blocks ofsamples. When all blocks of samples are coded in intra mode, thatpicture can be an intra picture. Intra pictures and their derivationssuch as independent decoder refresh pictures, can be used to reset thedecoder state and can, therefore, be used as the first picture in acoded video bitstream and a video session, or as a still image. Thesamples of an intra block can be exposed to a transform, and thetransform coefficients can be quantized before entropy coding. Intraprediction can be a technique that minimizes sample values in thepre-transform domain. In some cases, the smaller the DC value after atransform is, and the smaller the AC coefficients are, the fewer thebits that are required at a given quantization step size to representthe block after entropy coding.

Traditional intra coding such as known from, for example MPEG-2generation coding technologies, does not use intra prediction. However,some newer video compression technologies include techniques thatattempt, from, for example, surrounding sample data and/or metadataobtained during the encoding/decoding of spatially neighboring, andpreceding in decoding order, blocks of data. Such techniques arehenceforth called “intra prediction” techniques. Note that in at leastsome cases, intra prediction is only using reference data from thecurrent picture under reconstruction and not from reference pictures.

There can be many different forms of intra prediction. When more thanone of such techniques can be used in a given video coding technology,the technique in use can be coded in an intra prediction mode. Incertain cases, modes can have submodes and/or parameters, and those canbe coded individually or included in the mode codeword. Which codewordto use for a given mode/submode/parameter combination can have an impactin the coding efficiency gain through intra prediction, and so can theentropy coding technology used to translate the codewords into abitstream.

A certain mode of intra prediction was introduced with H.264, refined inH.265, and further refined in newer coding technologies such as jointexploration model (JEM), versatile video coding (VVC), and benchmark set(BMS). A predictor block can be formed using neighboring sample valuesbelonging to already available samples. Sample values of neighboringsamples are copied into the predictor block according to a direction. Areference to the direction in use can be coded in the bitstream or mayitself be predicted.

Motion compensation can be a lossy compression technique and can relateto techniques where a block of sample data from a previouslyreconstructed picture or part thereof (reference picture), after beingspatially shifted in a direction indicated by a motion vector (MVhenceforth), is used for the prediction of a newly reconstructed pictureor picture part. In some cases, the reference picture can be the same asthe picture currently under reconstruction. MVs can have two dimensionsX and Y, or three dimensions, the third being an indication of thereference picture in use (the latter, indirectly, can be a timedimension).

In some video compression techniques, an MV applicable to a certain areaof sample data can be predicted from other MVs, for example from thoserelated to another area of sample data spatially adjacent to the areaunder reconstruction, and preceding that MV in decoding order. Doing socan substantially reduce the amount of data required for coding the MV,thereby removing redundancy and increasing compression. MV predictioncan work effectively, for example, because when coding an input videosignal derived from a camera (known as natural video) there is astatistical likelihood that areas larger than the area to which a singleMV is applicable move in a similar direction and, therefore, can in somecases be predicted using a similar motion vector derived from MVs ofneighboring area. That results in the MV found for a given area to besimilar or the same as the MV predicted from the surrounding MVs, andthat in turn can be represented, after entropy coding, in a smallernumber of bits than what would be used if coding the MV directly. Insome cases, MV prediction can be an example of lossless compression of asignal (namely: the MVs) derived from the original signal (namely: thesample stream). In other cases, MV prediction itself can be lossy, forexample because of rounding errors when calculating a predictor fromseveral surrounding MVs.

Various MV prediction mechanisms are described in H.265/HEVC (ITU-T Rec.H.265, “High Efficiency Video Coding”, December 2016). Out of the manyMV prediction mechanisms that H.265 offers, described here is atechnique henceforth referred to as “spatial merge”.

Referring to FIG. 1 , a current block (101) comprises samples that havebeen found by the encoder during the motion search process to bepredictable from a previous block of the same size that has beenspatially shifted. Instead of coding that MV directly, the MV can bederived from metadata associated with one or more reference pictures,for example from the most recent (in decoding order) reference picture,using the MV associated with either one of five surrounding samples,denoted A0, A1, and B0, B1, B2 (102 through 106, respectively). InH.265, the MV prediction can use predictors from the same referencepicture that the neighboring block is using.

SUMMARY

According to an exemplary embodiment, a method of video decodingperformed in a video decoder includes receiving a coded video bitstreamincluding a current picture and at least one syntax element thatcorresponds to transform coefficients of a transform block in thecurrent picture. The method further includes determining an offset valuebased on an output of a monotonic non-decreasing f(x) function performedon a sum (x) of a group of partially reconstructed transformcoefficients. The method further includes determining a context modelindex based on a sum of the determined offset value and a base value.The method further includes selecting, for the at least one syntax of acurrent transform coefficient, a context model from a plurality ofcontext models based on the determined context model index.

According to an exemplary embodiment, a method of video decodingperformed in a video decoder includes receiving a coded video bitstreamincluding a current picture and at least one syntax element thatcorresponds to transform coefficients of a transform block in thecurrent picture. The method further includes determining, for eachcontext model region from a plurality of context model regions, anoutput of a monotonic non-decreasing function performed on a sum (x) ofa group of partially reconstructed transform coefficients and a numberof context models associated with a respective context model region. Themethod further includes determining a context model index based on theoutput of the monotonic non-decreasing function of each context modelregion. The method further includes selecting, for the at least onesyntax of a current transform coefficient, a context model from aplurality of context models based on the determined context model index.

According to an exemplary embodiment a video decoder for video decodingincludes processing circuitry configured to receive a coded videobitstream including a current picture and at least one syntax elementthat corresponds to transform coefficients of a transform block in thecurrent picture. The processing circuitry is further configured todetermine an offset value based on an output of a monotonicnon-decreasing f(x) function performed on a sum (x) of a group ofpartially reconstructed transform coefficients. The processing circuitryis further configured to determine a context model index based on a sumof the determined offset value and a base value. The processingcircuitry is further configured to select, for the at least one syntaxof a current transform coefficient, a context model from a plurality ofcontext models based on the determined context model index.

According to an exemplary embodiment, a video decoder apparatus forvideo decoding includes processing circuitry configured to receive acoded video bitstream including a current picture and at least onesyntax element that corresponds to transform coefficients of a transformblock in the current picture. The processing circuitry is furtherconfigured to determine, for each context model region from a pluralityof context model regions, an output of a monotonic non-decreasingfunction performed on a sum (x) of a group of partially reconstructedtransform coefficients and a number of context models associated with arespective context model region. The processing circuitry is furtherconfigured to determine a context model index based on the output of themonotonic non-decreasing function of each context model region. Theprocessing circuitry is further configured to select, for the at leastone syntax of a current transform coefficient, a context model from aplurality of context models based on the determined context model index.

BRIEF DESCRIPTION OF THE DRAWINGS

Further features, the nature, and various advantages of the disclosedsubject matter will be more apparent from the following detaileddescription and the accompanying drawings in which:

FIG. 1 is a schematic illustration of a current block and itssurrounding spatial merge candidates in one example.

FIG. 2 is a schematic illustration of a simplified block diagram of acommunication system in accordance with an embodiment.

FIG. 3 is a schematic illustration of a simplified block diagram of acommunication system in accordance with an embodiment.

FIG. 4 is a schematic illustration of a simplified block diagram of adecoder in accordance with an embodiment.

FIG. 5 is a schematic illustration of a simplified block diagram of anencoder in accordance with an embodiment.

FIG. 6 shows a block diagram of an encoder in accordance with anotherembodiment.

FIG. 7 shows a block diagram of a decoder in accordance with anotherembodiment.

FIG. 8A shows an exemplary context-based adaptive binary arithmeticcoding (CABAC) based entropy encoder in accordance with an embodiment.

FIG. 8B shows an exemplary CABAC based entropy decoder in accordancewith an embodiment.

FIG. 9 shows an example of a sub-block scan order in accordance with anembodiment.

FIG. 10 shows an example of a sub-block scanning process from whichdifferent types of syntax elements of transform coefficients aregenerated in accordance with an embodiment.

FIG. 11 shows an example of a local template used for context selectionfor current coefficients.

FIG. 12 shows diagonal positions of coefficients or coefficient levelsinside a coefficient block.

FIG. 13 illustrates a context index calculation for a luma component inaccordance with an embodiment.

FIG. 14 illustrates a context index calculation for a luma component inaccordance with an embodiment.

FIG. 15 illustrates a context index calculation for a luma component inaccordance with an embodiment.

FIG. 16 shows a flow chart outlining an entropy decoding process inaccordance with an embodiment.

FIG. 17 shows a flow chart outlining an entropy decoding process inaccordance with an embodiment.

FIG. 18 is a schematic illustration of a computer system in accordancewith an embodiment.

DETAILED DESCRIPTION OF EMBODIMENTS

FIG. 2 illustrates a simplified block diagram of a communication system(200) according to an embodiment of the present disclosure. Thecommunication system (200) includes a plurality of terminal devices thatcan communicate with each other, via, for example, a network (250). Forexample, the communication system (200) includes a first pair ofterminal devices (210) and (220) interconnected via the network (250).In the FIG. 2 example, the first pair of terminal devices (210) and(220) performs unidirectional transmission of data. For example, theterminal device (210) may code video data (e.g., a stream of videopictures that are captured by the terminal device (210)) fortransmission to the other terminal device (220) via the network (250).The encoded video data can be transmitted in the form of one or morecoded video bitstreams. The terminal device (220) may receive the codedvideo data from the network (250), decode the coded video data torecover the video pictures and display video pictures according to therecovered video data. Unidirectional data transmission may be common inmedia serving applications and the like.

In another example, the communication system (200) includes a secondpair of terminal devices (230) and (240) that performs bidirectionaltransmission of coded video data that may occur, for example, duringvideoconferencing. For bidirectional transmission of data, in anexample, each terminal device of the terminal devices (230) and (240)may code video data (e.g., a stream of video pictures that are capturedby the terminal device) for transmission to the other terminal device ofthe terminal devices (230) and (240) via the network (250). Eachterminal device of the terminal devices (230) and (240) also may receivethe coded video data transmitted by the other terminal device of theterminal devices (230) and (240), and may decode the coded video data torecover the video pictures and may display video pictures at anaccessible display device according to the recovered video data.

In the FIG. 2 example, the terminal devices (210), (220), (230) and(240) may be illustrated as servers, personal computers and smart phonesbut the principles of the present disclosure may be not so limited.Embodiments of the present disclosure find application with laptopcomputers, tablet computers, media players and/or dedicated videoconferencing equipment. The network (250) represents any number ofnetworks that convey coded video data among the terminal devices (210),(220), (230) and (240), including for example wireline (wired) and/orwireless communication networks. The communication network (250) mayexchange data in circuit-switched and/or packet-switched channels.Representative networks include telecommunications networks, local areanetworks, wide area networks and/or the Internet. For the purposes ofthe present discussion, the architecture and topology of the network(250) may be immaterial to the operation of the present disclosureunless explained herein below.

FIG. 3 illustrates, as an example for an application for the disclosedsubject matter, the placement of a video encoder and a video decoder ina streaming environment. The disclosed subject matter can be equallyapplicable to other video enabled applications, including, for example,video conferencing, digital TV, storing of compressed video on digitalmedia including CD, DVD, memory stick and the like, and so on.

A streaming system may include a capture subsystem (313), that caninclude a video source (301), for example a digital camera, creating forexample a stream of video pictures (302) that are uncompressed. In anexample, the stream of video pictures (302) includes samples that aretaken by the digital camera. The stream of video pictures (302),depicted as a bold line to emphasize a high data volume when compared toencoded video data (304) (or coded video bitstreams), can be processedby an electronic device (320) that includes a video encoder (303)coupled to the video source (301). The video encoder (303) can includehardware, software, or a combination thereof to enable or implementaspects of the disclosed subject matter as described in more detailbelow. The encoded video data (304) (or encoded video bitstream (304)),depicted as a thin line to emphasize the lower data volume when comparedto the stream of video pictures (302), can be stored on a streamingserver (305) for future use. One or more streaming client subsystems,such as client subsystems (306) and (308) in FIG. 3 can access thestreaming server (305) to retrieve copies (307) and (309) of the encodedvideo data (304). A client subsystem (306) can include a video decoder(310), for example, in an electronic device (330). The video decoder(310) decodes the incoming copy (307) of the encoded video data andcreates an outgoing stream of video pictures (311) that can be renderedon a display (312) (e.g., display screen) or other rendering device (notdepicted). In some streaming systems, the encoded video data (304),(307), and (309) (e.g., video bitstreams) can be encoded according tocertain video coding/compression standards. Examples of those standardsinclude ITU-T Recommendation H.265. In an example, a video codingstandard under development is informally known as Versatile Video Coding(VVC). The disclosed subject matter may be used in the context of VVC.

It is noted that the electronic devices (320) and (330) can includeother components (not shown). For example, the electronic device (320)can include a video decoder (not shown) and the electronic device (330)can include a video encoder (not shown) as well.

FIG. 4 shows a block diagram of a video decoder (410) according to anembodiment of the present disclosure. The video decoder (410) can beincluded in an electronic device (430). The electronic device (430) caninclude a receiver (431) (e.g., receiving circuitry). The video decoder(410) can be used in the place of the video decoder (310) in the FIG. 3example.

The receiver (431) may receive one or more coded video sequences to bedecoded by the video decoder (410); in the same or another embodiment,one coded video sequence at a time, where the decoding of each codedvideo sequence is independent from other coded video sequences. Thecoded video sequence may be received from a channel (401), which may bea hardware/software link to a storage device which stores the encodedvideo data. The receiver (431) may receive the encoded video data withother data, for example, coded audio data and/or ancillary data streams,that may be forwarded to their respective using entities (not depicted).The receiver (431) may separate the coded video sequence from the otherdata. To combat network jitter, a buffer memory (415) may be coupled inbetween the receiver (431) and an entropy decoder/parser (420) (“parser(420)” henceforth). In certain applications, the buffer memory (415) ispart of the video decoder (410). In others, it can be outside of thevideo decoder (410) (not depicted). In still others, there can be abuffer memory (not depicted) outside of the video decoder (410), forexample to combat network jitter, and in addition another buffer memory(415) inside the video decoder (410), for example to handle playouttiming. When the receiver (431) is receiving data from a store/forwarddevice of sufficient bandwidth and controllability, or from anisosynchronous network, the buffer memory (415) may not be needed, orcan be small. For use on best effort packet networks such as theInternet, the buffer memory (415) may be required, can be comparativelylarge and can be advantageously of adaptive size, and may at leastpartially be implemented in an operating system or similar elements (notdepicted) outside of the video decoder (410).

The video decoder (410) may include the parser (420) to reconstructsymbols (421) from the coded video sequence. Categories of those symbolsinclude information used to manage operation of the video decoder (410),and potentially information to control a rendering device such as arender device (412) (e.g., a display screen) that is not an integralpart of the electronic device (430) but can be coupled to the electronicdevice (430), as was shown in FIG. 4 . The control information for therendering device(s) may be in the form of Supplemental EnhancementInformation (SEI messages) or Video Usability Information (VUI)parameter set fragments (not depicted). The parser (420) mayparse/entropy-decode the coded video sequence that is received. Thecoding of the coded video sequence can be in accordance with a videocoding technology or standard, and can follow various principles,including variable length coding, Huffman coding, arithmetic coding withor without context sensitivity, and so forth. The parser (420) mayextract from the coded video sequence, a set of subgroup parameters forat least one of the subgroups of pixels in the video decoder, based uponat least one parameter corresponding to the group. Subgroups can includeGroups of Pictures (GOPs), pictures, tiles, slices, macroblocks, CodingUnits (CUs), blocks, Transform Units (TUs), Prediction Units (PUs) andso forth. The parser (420) may also extract from the coded videosequence information such as transform coefficients, quantizer parametervalues, motion vectors, and so forth.

The parser (420) may perform an entropy decoding/parsing operation onthe video sequence received from the buffer memory (415), so as tocreate symbols (421).

Reconstruction of the symbols (421) can involve multiple different unitsdepending on the type of the coded video picture or parts thereof (suchas: inter and intra picture, inter and intra block), and other factors.Which units are involved, and how, can be controlled by the subgroupcontrol information that was parsed from the coded video sequence by theparser (420). The flow of such subgroup control information between theparser (420) and the multiple units below is not depicted for clarity.

Beyond the functional blocks already mentioned, the video decoder (410)can be conceptually subdivided into a number of functional units asdescribed below. In a practical implementation operating undercommercial constraints, many of these units interact closely with eachother and can, at least partly, be integrated into each other. However,for the purpose of describing the disclosed subject matter, theconceptual subdivision into the functional units below is appropriate.

A first unit is the scaler/inverse transform unit (451). Thescaler/inverse transform unit (451) receives a quantized transformcoefficient as well as control information, including which transform touse, block size, quantization factor, quantization scaling matrices,etc. as symbol(s) (421) from the parser (420). The scaler/inversetransform unit (451) can output blocks comprising sample values, thatcan be input into aggregator (455).

In some cases, the output samples of the scaler/inverse transform (451)can pertain to an intra coded block; that is: a block that is not usingpredictive information from previously reconstructed pictures, but canuse predictive information from previously reconstructed parts of thecurrent picture. Such predictive information can be provided by an intrapicture prediction unit (452). In some cases, the intra pictureprediction unit (452) generates a block of the same size and shape ofthe block under reconstruction, using surrounding already reconstructedinformation fetched from the current picture buffer (458). The currentpicture buffer (458) buffers, for example, partly reconstructed currentpicture and/or fully reconstructed current picture. The aggregator(455), in some cases, adds, on a per sample basis, the predictioninformation the intra prediction unit (452) has generated to the outputsample information as provided by the scaler/inverse transform unit(451).

In other cases, the output samples of the scaler/inverse transform unit(451) can pertain to an inter coded, and potentially motion compensatedblock. In such a case, a motion compensation prediction unit (453) canaccess reference picture memory (457) to fetch samples used forprediction. After motion compensating the fetched samples in accordancewith the symbols (421) pertaining to the block, these samples can beadded by the aggregator (455) to the output of the scaler/inversetransform unit (451) (in this case called the residual samples orresidual signal) so as to generate output sample information. Theaddresses within the reference picture memory (457) from where themotion compensation prediction unit (453) fetches prediction samples canbe controlled by motion vectors, available to the motion compensationprediction unit (453) in the form of symbols (421) that can have, forexample X, Y, and reference picture components. Motion compensation alsocan include interpolation of sample values as fetched from the referencepicture memory (457) when sub-sample exact motion vectors are in use,motion vector prediction mechanisms, and so forth.

The output samples of the aggregator (455) can be subject to variousloop filtering techniques in the loop filter unit (456). Videocompression technologies can include in-loop filter technologies thatare controlled by parameters included in the coded video sequence (alsoreferred to as coded video bitstream) and made available to the loopfilter unit (456) as symbols (421) from the parser (420), but can alsobe responsive to meta-information obtained during the decoding ofprevious (in decoding order) parts of the coded picture or coded videosequence, as well as responsive to previously reconstructed andloop-filtered sample values.

The output of the loop filter unit (456) can be a sample stream that canbe output to the render device (412) as well as stored in the referencepicture memory (457) for use in future inter-picture prediction.

Certain coded pictures, once fully reconstructed, can be used asreference pictures for future prediction. For example, once a codedpicture corresponding to a current picture is fully reconstructed andthe coded picture has been identified as a reference picture (by, forexample, the parser (420)), the current picture buffer (458) can becomea part of the reference picture memory (457), and a fresh currentpicture buffer can be reallocated before commencing the reconstructionof the following coded picture.

The video decoder (410) may perform decoding operations according to apredetermined video compression technology in a standard, such as ITU-TRec. H.265. The coded video sequence may conform to a syntax specifiedby the video compression technology or standard being used, in the sensethat the coded video sequence adheres to both the syntax of the videocompression technology or standard and the profiles as documented in thevideo compression technology or standard. Specifically, a profile canselect certain tools as the only tools available for use under thatprofile from all the tools available in the video compression technologyor standard. Also necessary for compliance can be that the complexity ofthe coded video sequence is within bounds as defined by the level of thevideo compression technology or standard. In some cases, levels restrictthe maximum picture size, maximum frame rate, maximum reconstructionsample rate (measured in, for example megasamples per second), maximumreference picture size, and so on. Limits set by levels can, in somecases, be further restricted through Hypothetical Reference Decoder(HRD) specifications and metadata for HRD buffer management signaled inthe coded video sequence.

In an embodiment, the receiver (431) may receive additional (redundant)data with the encoded video. The additional data may be included as partof the coded video sequence(s). The additional data may be used by thevideo decoder (410) to properly decode the data and/or to moreaccurately reconstruct the original video data. Additional data can bein the form of, for example, temporal, spatial, or signal noise ratio(SNR) enhancement layers, redundant slices, redundant pictures, forwarderror correction codes, and so on.

FIG. 5 shows a block diagram of a video encoder (503) according to anembodiment of the present disclosure. The video encoder (503) isincluded in an electronic device (520). The electronic device (520)includes a transmitter (540) (e.g., transmitting circuitry). The videoencoder (503) can be used in the place of the video encoder (303) in theFIG. 3 example.

The video encoder (503) may receive video samples from a video source(501) (that is not part of the electronic device (520) in the FIG. 5example) that may capture video image(s) to be coded by the videoencoder (503). In another example, the video source (501) is a part ofthe electronic device (520).

The video source (501) may provide the source video sequence to be codedby the video encoder (503) in the form of a digital video sample streamthat can be of any suitable bit depth (for example: 8 bit, 10 bit, 12bit, . . . ), any colorspace (for example, BT.601 Y CrCB, RGB, . . . ),and any suitable sampling structure (for example Y CrCb 4:2:0, Y CrCb4:4:4). In a media serving system, the video source (501) may be astorage device storing previously prepared video. In a videoconferencingsystem, the video source (501) may be a camera that captures local imageinformation as a video sequence. Video data may be provided as aplurality of individual pictures that impart motion when viewed insequence. The pictures themselves may be organized as a spatial array ofpixels, wherein each pixel can comprise one or more samples depending onthe sampling structure, color space, etc. in use. A person skilled inthe art can readily understand the relationship between pixels andsamples. The description below focuses on samples.

According to an embodiment, the video encoder (503) may code andcompress the pictures of the source video sequence into a coded videosequence (543) in real time or under any other time constraints asrequired by the application. Enforcing appropriate coding speed is onefunction of a controller (550). In some embodiments, the controller(550) controls other functional units as described below and isfunctionally coupled to the other functional units. The coupling is notdepicted for clarity. Parameters set by the controller (550) can includerate control related parameters (picture skip, quantizer, lambda valueof rate-distortion optimization techniques, . . . ), picture size, groupof pictures (GOP) layout, maximum motion vector search range, and soforth. The controller (550) can be configured to have other suitablefunctions that pertain to the video encoder (503) optimized for acertain system design.

In some embodiments, the video encoder (503) is configured to operate ina coding loop. As an oversimplified description, in an example, thecoding loop can include a source coder (530) (e.g., responsible forcreating symbols, such as a symbol stream, based on an input picture tobe coded, and a reference picture(s)), and a (local) decoder (533)embedded in the video encoder (503). The decoder (533) reconstructs thesymbols to create the sample data in a similar manner as a (remote)decoder also would create (as any compression between symbols and codedvideo bitstream is lossless in the video compression technologiesconsidered in the disclosed subject matter). The reconstructed samplestream (sample data) is input to the reference picture memory (534). Asthe decoding of a symbol stream leads to bit-exact results independentof decoder location (local or remote), the content in the referencepicture memory (534) is also bit exact between the local encoder andremote encoder. In other words, the prediction part of an encoder “sees”as reference picture samples exactly the same sample values as a decoderwould “see” when using prediction during decoding. This fundamentalprinciple of reference picture synchronicity (and resulting drift, ifsynchronicity cannot be maintained, for example because of channelerrors) is used in some related arts as well.

The operation of the “local” decoder (533) can be the same as of a“remote” decoder, such as the video decoder (410), which has alreadybeen described in detail above in conjunction with FIG. 4 . Brieflyreferring also to FIG. 4 , however, as symbols are available andencoding/decoding of symbols to a coded video sequence by an entropycoder (545) and the parser (420) can be lossless, the entropy decodingparts of the video decoder (410), including the buffer memory (415), andparser (420) may not be fully implemented in the local decoder (533).

An observation that can be made at this point is that any decodertechnology except the parsing/entropy decoding that is present in adecoder also necessarily needs to be present, in substantially identicalfunctional form, in a corresponding encoder. For this reason, thedisclosed subject matter focuses on decoder operation. The descriptionof encoder technologies can be abbreviated as they are the inverse ofthe comprehensively described decoder technologies. Only in certainareas a more detail description is required and provided below.

During operation, in some examples, the source coder (530) may performmotion compensated predictive coding, which codes an input picturepredictively with reference to one or more previously-coded picture fromthe video sequence that were designated as “reference pictures”. In thismanner, the coding engine (532) codes differences between pixel blocksof an input picture and pixel blocks of reference picture(s) that may beselected as prediction reference(s) to the input picture.

The local video decoder (533) may decode coded video data of picturesthat may be designated as reference pictures, based on symbols createdby the source coder (530). Operations of the coding engine (532) mayadvantageously be lossy processes. When the coded video data may bedecoded at a video decoder (not shown in FIG. 5 ), the reconstructedvideo sequence typically may be a replica of the source video sequencewith some errors. The local video decoder (533) replicates decodingprocesses that may be performed by the video decoder on referencepictures and may cause reconstructed reference pictures to be stored inthe reference picture cache (534). In this manner, the video encoder(503) may store copies of reconstructed reference pictures locally thathave common content as the reconstructed reference pictures that will beobtained by a far-end video decoder (absent transmission errors).

The predictor (535) may perform prediction searches for the codingengine (532). That is, for a new picture to be coded, the predictor(535) may search the reference picture memory (534) for sample data (ascandidate reference pixel blocks) or certain metadata such as referencepicture motion vectors, block shapes, and so on, that may serve as anappropriate prediction reference for the new pictures. The predictor(535) may operate on a sample block-by-pixel block basis to findappropriate prediction references. In some cases, as determined bysearch results obtained by the predictor (535), an input picture mayhave prediction references drawn from multiple reference pictures storedin the reference picture memory (534).

The controller (550) may manage coding operations of the source coder(530), including, for example, setting of parameters and subgroupparameters used for encoding the video data.

Output of all aforementioned functional units may be subjected toentropy coding in the entropy coder (545). The entropy coder (545)translates the symbols as generated by the various functional units intoa coded video sequence, by lossless compressing the symbols according totechnologies such as Huffman coding, variable length coding, arithmeticcoding, and so forth.

The transmitter (540) may buffer the coded video sequence(s) as createdby the entropy coder (545) to prepare for transmission via acommunication channel (560), which may be a hardware/software link to astorage device which would store the encoded video data. The transmitter(540) may merge coded video data from the video coder (503) with otherdata to be transmitted, for example, coded audio data and/or ancillarydata streams (sources not shown).

The controller (550) may manage operation of the video encoder (503).During coding, the controller (550) may assign to each coded picture acertain coded picture type, which may affect the coding techniques thatmay be applied to the respective picture. For example, pictures oftenmay be assigned as one of the following picture types:

An Intra Picture (I picture) may be one that may be coded and decodedwithout using any other picture in the sequence as a source ofprediction. Some video codecs allow for different types of intrapictures, including, for example Independent Decoder Refresh (“IDR”)Pictures. A person skilled in the art is aware of those variants of Ipictures and their respective applications and features.

A predictive picture (P picture) may be one that may be coded anddecoded using intra prediction or inter prediction using at most onemotion vector and reference index to predict the sample values of eachblock.

A bi-directionally predictive picture (B Picture) may be one that may becoded and decoded using intra prediction or inter prediction using atmost two motion vectors and reference indices to predict the samplevalues of each block. Similarly, multiple-predictive pictures can usemore than two reference pictures and associated metadata for thereconstruction of a single block.

Source pictures commonly may be subdivided spatially into a plurality ofsample blocks (for example, blocks of 4×4, 8×8, 4×8, or 16×16 sampleseach) and coded on a block-by-block basis. Blocks may be codedpredictively with reference to other (already coded) blocks asdetermined by the coding assignment applied to the blocks' respectivepictures. For example, blocks of I pictures may be codednon-predictively or they may be coded predictively with reference toalready coded blocks of the same picture (spatial prediction or intraprediction). Pixel blocks of P pictures may be coded predictively, viaspatial prediction or via temporal prediction with reference to onepreviously coded reference picture. Blocks of B pictures may be codedpredictively, via spatial prediction or via temporal prediction withreference to one or two previously coded reference pictures.

The video encoder (503) may perform coding operations according to apredetermined video coding technology or standard, such as ITU-T Rec.H.265. In its operation, the video encoder (503) may perform variouscompression operations, including predictive coding operations thatexploit temporal and spatial redundancies in the input video sequence.The coded video data, therefore, may conform to a syntax specified bythe video coding technology or standard being used.

In an embodiment, the transmitter (540) may transmit additional datawith the encoded video. The source coder (530) may include such data aspart of the coded video sequence. Additional data may comprisetemporal/spatial/SNR enhancement layers, other forms of redundant datasuch as redundant pictures and slices, SEI messages, VUI parameter setfragments, and so on.

A video may be captured as a plurality of source pictures (videopictures) in a temporal sequence. Intra-picture prediction (oftenabbreviated to intra prediction) makes use of spatial correlation in agiven picture, and inter-picture prediction makes uses of the (temporalor other) correlation between the pictures. In an example, a specificpicture under encoding/decoding, which is referred to as a currentpicture, is partitioned into blocks. When a block in the current pictureis similar to a reference block in a previously coded and still bufferedreference picture in the video, the block in the current picture can becoded by a vector that is referred to as a motion vector. The motionvector points to the reference block in the reference picture, and canhave a third dimension identifying the reference picture, in casemultiple reference pictures are in use.

In some embodiments, a bi-prediction technique can be used in theinter-picture prediction. According to the bi-prediction technique, tworeference pictures, such as a first reference picture and a secondreference picture that are both prior in decoding order to the currentpicture in the video (but may be in the past and future, respectively,in display order) are used. A block in the current picture can be codedby a first motion vector that points to a first reference block in thefirst reference picture, and a second motion vector that points to asecond reference block in the second reference picture. The block can bepredicted by a combination of the first reference block and the secondreference block.

Further, a merge mode technique can be used in the inter-pictureprediction to improve coding efficiency.

According to some embodiments of the disclosure, predictions, such asinter-picture predictions and intra-picture predictions are performed inthe unit of blocks. For example, according to the HEVC standard, apicture in a sequence of video pictures is partitioned into coding treeunits (CTU) for compression, the CTUs in a picture have the same size,such as 64×64 pixels, 32×32 pixels, or 16×16 pixels. In general, a CTUincludes three coding tree blocks (CTBs), which are one luma CTB and twochroma CTBs. Each CTU can be recursively quadtree split into one ormultiple coding units (CUs). For example, a CTU of 64×64 pixels can besplit into one CU of 64×64 pixels, or 4 CUs of 32×32 pixels, or 16 CUsof 16×16 pixels. In an example, each CU is analyzed to determine aprediction type for the CU, such as an inter prediction type or an intraprediction type. The CU is split into one or more prediction units (PUs)depending on the temporal and/or spatial predictability. Generally, eachPU includes a luma prediction block (PB), and two chroma PBs. In anembodiment, a prediction operation in coding (encoding/decoding) isperformed in the unit of a prediction block. Using a luma predictionblock as an example of a prediction block, the prediction block includesa matrix of values (e.g., luma values) for pixels, such as 8×8 pixels,16×16 pixels, 8×16 pixels, 16×8 pixels, and the like.

FIG. 6 shows a diagram of a video encoder (603) according to anotherembodiment of the disclosure. The video encoder (603) is configured toreceive a processing block (e.g., a prediction block) of sample valueswithin a current video picture in a sequence of video pictures, andencode the processing block into a coded picture that is part of a codedvideo sequence. In an example, the video encoder (603) is used in theplace of the video encoder (303) in the FIG. 3 example.

In an HEVC example, the video encoder (603) receives a matrix of samplevalues for a processing block, such as a prediction block of 8×8samples, and the like. The video encoder (603) determines whether theprocessing block is best coded using intra mode, inter mode, orbi-prediction mode using, for example, rate-distortion optimization.When the processing block is to be coded in intra mode, the videoencoder (603) may use an intra prediction technique to encode theprocessing block into the coded picture; and when the processing blockis to be coded in inter mode or bi-prediction mode, the video encoder(603) may use an inter prediction or bi-prediction technique,respectively, to encode the processing block into the coded picture. Incertain video coding technologies, merge mode can be an inter pictureprediction submode where the motion vector is derived from one or moremotion vector predictors without the benefit of a coded motion vectorcomponent outside the predictors. In certain other video codingtechnologies, a motion vector component applicable to the subject blockmay be present. In an example, the video encoder (603) includes othercomponents, such as a mode decision module (not shown) to determine themode of the processing blocks.

In the FIG. 6 example, the video encoder (603) includes the interencoder (630), an intra encoder (622), a residue calculator (623), aswitch (626), a residue encoder (624), a general controller (621), andan entropy encoder (625) coupled together as shown in FIG. 6 .

The inter encoder (630) is configured to receive the samples of thecurrent block (e.g., a processing block), compare the block to one ormore reference blocks in reference pictures (e.g., blocks in previouspictures and later pictures), generate inter prediction information(e.g., description of redundant information according to inter encodingtechnique, motion vectors, merge mode information), and calculate interprediction results (e.g., predicted block) based on the inter predictioninformation using any suitable technique. In some examples, thereference pictures are decoded reference pictures that are decoded basedon the encoded video information.

The intra encoder (622) is configured to receive the samples of thecurrent block (e.g., a processing block), in some cases compare theblock to blocks already coded in the same picture, generate quantizedcoefficients after transform, and in some cases also intra predictioninformation (e.g., an intra prediction direction information accordingto one or more intra encoding techniques). In an example, the intraencoder (622) also calculates intra prediction results (e.g., predictedblock) based on the intra prediction information and reference blocks inthe same picture.

The general controller (621) is configured to determine general controldata and control other components of the video encoder (603) based onthe general control data. In an example, the general controller (621)determines the mode of the block, and provides a control signal to theswitch (626) based on the mode. For example, when the mode is the intramode, the general controller (621) controls the switch (626) to selectthe intra mode result for use by the residue calculator (623), andcontrols the entropy encoder (625) to select the intra predictioninformation and include the intra prediction information in thebitstream; and when the mode is the inter mode, the general controller(621) controls the switch (626) to select the inter prediction resultfor use by the residue calculator (623), and controls the entropyencoder (625) to select the inter prediction information and include theinter prediction information in the bitstream.

The residue calculator (623) is configured to calculate a difference(residue data) between the received block and prediction resultsselected from the intra encoder (622) or the inter encoder (630). Theresidue encoder (624) is configured to operate based on the residue datato encode the residue data to generate the transform coefficients. In anexample, the residue encoder (624) is configured to convert the residuedata from a spatial domain to a frequency domain, and generate thetransform coefficients. The transform coefficients are then subject toquantization processing to obtain quantized transform coefficients. Invarious embodiments, the video encoder (603) also includes a residuedecoder (628). The residue decoder (628) is configured to performinverse-transform, and generate the decoded residue data. The decodedresidue data can be suitably used by the intra encoder (622) and theinter encoder (630). For example, the inter encoder (630) can generatedecoded blocks based on the decoded residue data and inter predictioninformation, and the intra encoder (622) can generate decoded blocksbased on the decoded residue data and the intra prediction information.The decoded blocks are suitably processed to generate decoded picturesand the decoded pictures can be buffered in a memory circuit (not shown)and used as reference pictures in some examples.

The entropy encoder (625) is configured to format the bitstream toinclude the encoded block. The entropy encoder (625) is configured toinclude various information according to a suitable standard, such asthe HEVC standard. In an example, the entropy encoder (625) isconfigured to include the general control data, the selected predictioninformation (e.g., intra prediction information or inter predictioninformation), the residue information, and other suitable information inthe bitstream. Note that, according to the disclosed subject matter,when coding a block in the merge submode of either inter mode orbi-prediction mode, there is no residue information.

FIG. 7 shows a diagram of a video decoder (710) according to anotherembodiment of the disclosure. The video decoder (710) is configured toreceive coded pictures that are part of a coded video sequence, anddecode the coded pictures to generate reconstructed pictures. In anexample, the video decoder (710) is used in the place of the videodecoder (310) in the FIG. 3 example.

In the FIG. 7 example, the video decoder (710) includes an entropydecoder (771), an inter decoder (780), a residue decoder (773), areconstruction module (774), and an intra decoder (772) coupled togetheras shown in FIG. 7 .

The entropy decoder (771) can be configured to reconstruct, from thecoded picture, certain symbols that represent the syntax elements ofwhich the coded picture is made up. Such symbols can include, forexample, the mode in which a block is coded (such as, for example, intramode, inter mode, bi-predicted mode, the latter two in merge submode oranother submode), prediction information (such as, for example, intraprediction information or inter prediction information) that canidentify certain sample or metadata that is used for prediction by theintra decoder (772) or the inter decoder (780), respectively, residualinformation in the form of, for example, quantized transformcoefficients, and the like. In an example, when the prediction mode isinter or bi-predicted mode, the inter prediction information is providedto the inter decoder (780); and when the prediction type is the intraprediction type, the intra prediction information is provided to theintra decoder (772). The residual information can be subject to inversequantization and is provided to the residue decoder (773).

The inter decoder (780) is configured to receive the inter predictioninformation, and generate inter prediction results based on the interprediction information.

The intra decoder (772) is configured to receive the intra predictioninformation, and generate prediction results based on the intraprediction information.

The residue decoder (773) is configured to perform inverse quantizationto extract de-quantized transform coefficients, and process thede-quantized transform coefficients to convert the residual from thefrequency domain to the spatial domain. The residue decoder (773) mayalso require certain control information (to include the QuantizerParameter (QP)), and that information may be provided by the entropydecoder (771) (data path not depicted as this may be low volume controlinformation only).

The reconstruction module (774) is configured to combine, in the spatialdomain, the residual as output by the residue decoder (773) and theprediction results (as output by the inter or intra prediction modulesas the case may be) to form a reconstructed block, that may be part ofthe reconstructed picture, which in turn may be part of thereconstructed video. It is noted that other suitable operations, such asa deblocking operation and the like, can be performed to improve thevisual quality.

It is noted that the video encoders (303), (503), and (603), and thevideo decoders (310), (410), and (710) can be implemented using anysuitable technique. In an embodiment, the video encoders (303), (503),and (603), and the video decoders (310), (410), and (710) can beimplemented using one or more integrated circuits. In anotherembodiment, the video encoders (303), (503), and (603), and the videodecoders (310), (410), and (710) can be implemented using one or moreprocessors that execute software instructions.

Entropy coding can be performed at a last stage of video coding (or afirst stage of video decoding) after a video signal is reduced to aseries of syntax elements. Entropy coding can be a lossless compressionscheme that uses statistic properties to compress data such that anumber of bits used to represent the data is logarithmicallyproportional to the probability of the data. For example, by performingentropy coding over a set of syntax elements, bits representing thesyntax elements (referred to as bins) can be converted to fewer bits(referred to as coded bits) in a bit stream. Context-based adaptivebinary arithmetic coding (CABAC) is one form of entropy coding. InCABAC, a context model providing a probability estimate can bedetermined for each bin in a sequence of bins based on a contextassociated with the respective bin. Subsequently, a binary arithmeticcoding process can be performed using the probability estimates toencode the sequence of bins to coded bits in a bit stream. In addition,the context model is updated with a new probability estimate based onthe coded bin.

FIG. 8A shows an exemplary CABAC based entropy encoder (800A) inaccordance with an embodiment. For example, the entropy encoder (800A)can be implemented in the entropy coder (545) in the FIG. 5 example, orthe entropy encoder (625) in the FIG. 6 example. The entropy encoder(800A) can include a context modeler (810) and a binary arithmeticencoder (820). In an example, various types of syntax elements areprovided as input to the entropy encoder (800A). For example, a bin of abinary valued syntax element can be directly input to the contextmodeler (810), while a non-binary valued syntax element can first bebinarized to a bin string before bins of the bin string are input to thecontext modeler (810).

In an example, the context modeler (810) receives bins of syntaxelements, and performs a context modeling process to select a contextmodel for each received bin. For example, a bin of a binary syntaxelement of a transform coefficient in a transform block is received. Acontext model can accordingly be determined for this bin based, forexample, on a type of the syntax element, a color component type of thetransform component, a location of the transform coefficient, andpreviously processed neighboring transform coefficients, and the like.The context model can provide a probability estimate for this bin.

In an example, a set of context models can be configured for each typeof syntax elements. Those context models can be arranged in a contextmodel list (802) that is stored in a memory (801) as shown in FIG. 8A.Each entry in the context model list (802) can represent a contextmodel. Each context model on the list can be assigned an index, referredto as a context model index, or context index. In addition, each contextmodel can include a probability estimate, or parameters indicating aprobability estimate. The probability estimate can indicate a likelihoodof a bin being 0 or 1. For example, during the context modeling, thecontext modeler (810) can calculate a context index for a bin, and acontext model can accordingly be selected according to the context indexfrom the context model list (802) and assigned to the bin.

Moreover, probability estimates in the context model list can beinitialized at the start of the operation of the entropy encoder (800A).After a context model on the context model list (802) is assigned to abin and used for encoding the bin, the context model can subsequently beupdated according to a value of the bin with an updated probabilityestimate.

In an example, the binary arithmetic encoder (820) receives bins andcontext models (e.g., probability estimates) assigned to the bins, andaccordingly performs a binary arithmetic coding process. As a result,coded bits are generated and transmitted in a bit stream.

FIG. 8B shows an exemplary CABAC based entropy decoder (800B) inaccordance with an embodiment. For example, the entropy decoder (800B)can be implemented in the parser (420) in the FIG. 4 example, or theentropy decoder (771) in the FIG. 7 example. The entropy decoder (800B)can include a binary arithmetic decoder (830), and a context modeler(840). The binary arithmetic decoder (830) receives coded bits from abit stream, and performs a binary arithmetic decoding process to recoverbins from the coded bits. The context modeler (840) can operatesimilarly to the context modeler (810). For example, the context modeler(840) can select context models in a context model list (804) stored ina memory (803), and provide the selected context models to the binaryarithmetic decoder (830). However, the context modeler (840) determinesthe context models based on the recovered bins from the binaryarithmetic decoder (830). For example, based on the recovered bins, thecontext modeler (840) can know a type of a syntax element of a nextto-be-decoded bin, and values of previously decoded syntax elements.That information is used for determining a context model for the nextto-be-decoded bin.

In an embodiment, residual signals of a transform block are firsttransformed from spatial domain to frequency domain resulting in a blockof transform coefficients. Then, a quantization is performed to quantizethe block of transform coefficients into a block of transformcoefficient levels. In various embodiments, different techniques may beused for converting residual signals into transform coefficient levels.The block of transform coefficient levels is further processed togenerate syntax elements that can be provided to an entropy encoder andencoded into bits of a bit stream. In an embodiment, a process ofgenerating the syntax elements from the transform coefficient levels canbe performed in the following way.

The block of transform coefficient levels can first be split intosub-blocks, for example, with a size of 4×4 positions. Those sub-blockscan be processed according to a predefined scan order. FIG. 9 shows anexample of the sub-block scan order, referred to as an inverse diagonalscan order. As shown, a block (910) is partitioned into 16 sub-blocks(901). The sub-block at the bottom-right corner is first processed,while the sub-block at the top-left corner is last processed. For asub-block within which the transform coefficient levels are all zero,the sub-block can be skipped without processing in an example.

For sub-blocks each having at least one non-zero transform coefficientlevel, four passes of scan can be performed in each sub-block. Duringeach pass, the 16 positions in the respective sub-block can be scannedin the inverse diagonal scan order. FIG. 10 shows an example of asub-block scanning process (1000) from which different types of syntaxelements of transform coefficients are generated.

Sixteen coefficient positions (1010) inside a sub-block are shown in onedimension at the bottom of FIG. 10 . The positions (1010) are numberedfrom 0 to 15 reflecting the respective scan order. During a first pass,the scan positions (1010) are scanned over, and three types of syntaxelements (1001-1003) can possibly be generated at each scan position(1010):

-   -   (i) A first type of binary syntax elements (1001) (referred to        as significance flags and denoted by sig_coeff_flag) indicating        whether an absolute transform coefficient level of the        respective transform coefficient (denoted by absLevel) is zero        or larger than zero.    -   (ii) A second type of binary syntax elements (1002) (referred to        as parity flags and denoted by par_level_flag) indicating a        parity of the absolute transform coefficient level of the        respective transform coefficient. The parity flags are generated        only when the absolute transform coefficient level of the        respective transform coefficient is non-zero.    -   (iii) A third type of binary syntax elements (1003) (referred to        as greater 1 flags and denoted by rem_abs_gt1_flag) indicating        whether (absLevel−1)>>1 is greater than 0 for the respective        transform coefficient. The greater 1 flags are generated only        when the absolute transform coefficient level of the respective        transform coefficient is non-zero.

During a second pass, a fourth type of binary syntax elements (1004) canpossibly be generated. The fourth type of syntax elements (1004) isreferred to as greater 2 flags and denoted by rem_abs_gt2_flag. Thefourth type of syntax elements (1004) indicates whether the absolutetransform coefficient level of the respective transform coefficient isgreater than 4. The greater 2 flags are generated only when(absLevel−1)>>1 is greater than 0 for the respective transformcoefficient.

During a third pass, a fifth type of non-binary syntax elements (1005)can possibly be generated. The fifth type of syntax elements (1005) isdenoted by abs_remainder, and indicates a remaining value of theabsolute transform coefficient level of the respective transformcoefficient that is greater than 4. The fifth type of syntax elements(1005) are generated only when the absolute transform coefficient levelof the respective transform coefficient is greater than 4.

During a fourth pass, a sixth type of syntax elements (1006) can begenerated at each scan position (1010) with a non-zero coefficient levelindicating a sign of the respective transform coefficient level.

The above described various types of syntax elements (1001-1006) can beprovided to an entropy encoder according to the order of the passes andthe scan order in each pass. Different entropy encoding schemes can beemployed for encoding different types of syntax elements. For example,in an embodiment, the significance flags, parity flags, greater 1 flags,and greater 2 flags can be encoded with a CABAC based entropy encoder,such as that described in the FIG. 8A example. In contrast, the syntaxelements generated during the third and fourth passes can be encodedwith a CABAC-bypassed entropy encoder (e.g., a binary arithmetic encoderwith fixed probability estimates for input bins).

Context modeling can be performed to determine context models for binsof some types of transform coefficient syntax elements. In anembodiment, the context models can be determined according to a localtemplate and a diagonal position of each current coefficient (e.g., acoefficient currently under processing) possibly in combination withother factors.

FIG. 11 shows an example of a local template (1130) used for contextselection for current coefficients. The local template (1130) can covera set of neighboring positions or coefficients of a current coefficient(1120) in a coefficient block (1110). In the FIG. 11 example, thecoefficient block (1110) has a size of 8×8 positions, and includecoefficient levels at the 64 positions. The coefficient block (1110) ispartitioned into 4 sub-blocks each with a size of 4×4 positions. In theFIG. 11 example, the local template (1130) is defined to be a 5 positiontemplate covering 5 coefficient levels at the bottom-right side of thecurrent coefficient (1120). When an inverse diagonal scan order is usedfor multiple passes over the scan positions within the coefficient block(1110), the neighboring positions within the local template (1130) areprocessed prior to the current coefficient (1120).

During the context modeling, information of the coefficient levelswithin the local template (1130) can be used to determine a contextmodel. For this purpose, a measure, referred to as a template magnitude,is defined in some embodiments to measure or indicate magnitudes of thetransform coefficients or transform coefficient levels within the localtemplate (1130). The template magnitude can then be used as the basisfor select the context model.

In one example, the template magnitude is defined to be a sum, denotedby sumAbs1, of partially reconstructed absolute transform coefficientlevels inside the local template (1130). A partially reconstructedabsolute transform coefficient level can be determined according to binsof the syntax elements, sig_coeff_flag, par_level_flag, andrem_abs_gt1_flag of the respective transform coefficient. These threetypes of syntax elements are obtained after a first pass over scanpositions of a sub-block performed in an entropy encoder or an entropydecoder. In an embodiment, a partially reconstructed absolute transformcoefficient level at a position (x, y) can be determined according to:absLevel1[x][y]=sig_coeff_flag[x][y]+par_level_flag[x][y]+2*rem_abs_gt1_flag[x][y],  Eq.(1):where x and y are coordinates with respect to a top-left corner of thecoefficient block (1110), while absLevel1[x][y] represents the partiallyreconstructed absolute transform coefficient level at the position (x,y).

In another example, the template magnitude is defined to be adifference, denoted by tmplCpSum1, between the sum of the partiallyreconstructed absolute transform coefficient levels and the number,denoted by numSig, of non-zero coefficients in the local template(1130). Thus, the difference can be determined according to:tmplCpSum1=sumAbs1−numSig.  Eq. (2):

In other examples, the template magnitude may be defined in other waysto indicate magnitudes of transform coefficients or transformcoefficient levels.

In some embodiments, to exploit a correlation between transformcoefficients, the previously coded coefficients covered by a localtemplate shown in FIG. 11 are used in the context selection for thecurrent coefficients, where the position with square cross-hatching(1120) indicates the current transform coefficient position (x, y) andthe positions with diagonal cross-hatching indicates its five neighbors.Let AbsLevelPass1[x][y] represent the partially reconstructed absolutelevels for coefficient at position (x, y) after the first pass, drepresents the diagonal position of the current coefficient (d=x+y),sumAbs1 represents the sum of partially reconstructed absolute levelAbsLevelPass1[x][y] of coefficients covered by local template. Thesyntax element AbsLevelPass1[x][y] may be computed from the syntaxelements sig_coeff_flag[xC][yC], abs_level_gtx_flag[n][0],par_level_flag[n], abs_level_gtx_flag[n][1], whereabs_level_gtx_flag[n][0] and abs_level_gtx_flag[n][1] are also known asrem_abs_gt1_flag and rem_abs_gt2_flag respectively for the coefficientat position n in FIG. 10 .

FIG. 12 shows diagonal positions of coefficients or coefficient levelsinside a coefficient block (1210). In an embodiment, the diagonalposition of a scan position (x, y) is defined according to:d=x+y,  Eq. (3):where d represents the diagonal position, and x and y are coordinates ofthe respective position. The diagonal position, d, of each coefficientcan be used to define different frequency regions within the coefficientblock (1210) based on one or two diagonal position thresholds. As twoexamples, a low frequency region (1220) is defined with d<=3, while ahigh frequency region (1230) is defined with d>=11, as shown in FIG. 12.

In some embodiments, when coding sig_coeff_flag[x][y] of the currentcoefficient, a context model index is selected depending on a value ofsumAbs1 and a diagonal position d. More specifically, as shown in FIG.13 for a Luma component, the context model index is determined accordingto:offset=min(sumAbs1,5)  Eq. (4):base=18*max(0,state−1)+(d<2?12:(d<5?6:0))  Eq. (5):ctxSig=base+offset  Eq. (6):

For a Chroma component, the context model index is determined accordingto:offset=min(sumAbs1,5)  Eq. (7):base=12*max(0,state−1)+(d<2?6:0)  Eq. (8):ctxSig=base+offset,  Eq. (9):

where state specifies the scalar quantizer used, and the operators ? and: are defined as in the computer language C. If the dependentquantization is enabled, state is derived using a state transitionprocess. Otherwise, dependent quantization is not enabled, state isequal to 0.

In some examples, the number of context models for codingsig_coeff_flag[x][y] is 54 for Luma and 36 for Chroma. Therefore, thetotal number of context models for coding sig_coeff_flag[x][y] is 90,which is more than 21% of the 424 context models in standardized contextmodeling schemes such as VVC Draft 5.

Table 1 illustrates an example of a residual coding syntax. In Table 1,xC corresponds to an x coordinate of a current coefficient in atransform block, and yC corresponds to a y coordinate of the currentcoefficient in the transform block.

TABLE 1 Descriptor residual_coding( x0, y0, log2TbWidth, log2TbHeight,cIdx ) {  if( (tu_mts_idx[ x0 ][ y0 ] > 0 | |    ( cu_sbt_flag &&log2TbWidth < 6 && log2TbHeight < 6 ) )    && cIdx = = 0 &&log2TbWidth > 4 )   log2ZoTbWidth = 4  Else   log2ZoTbWidth = Min(log2TbWidth, 5 )  if( tu_mts_idx[ x0 ][ y0 ] > 0 | |    ( cu_sbt_flag &&log2TbWidth < 6 && log2TbHeight < 6 ) )    && cIdx = = 0 &&log2TbHeight > 4 )   log2ZoTbHeight = 4  Else   log2ZoTbHeight = Min(log2TbHeight, 5 )  if( log2TbWidth > 0 )   last_sig_coeff_x_prefix ae(v) if( log2TbHeight > 0 )   last_sig_coeff_y_prefix ae(v)  if(last_sig_coeff_x_prefix > 3 )   last_sig_coeff_x_suffix ae(v)  if(last_sig_coeff_y_prefix > 3 )   last_sig_coeff_y_suffix ae(v) log2TbWidth = log2ZoTbWidth  log2TbHeight = log2ZoTbHeight  log2SbW =(Min( log2TbWidth, log2TbHeight ) < 2 ? 1 : 2 )  log2SbH = log2SbW  if(log2TbWidth + log2TbHeight > 3 ) {   if( log2TbWidth < 2 ) {    log2SbW= log2Tb Width    log2SbH = 4 − log2SbW   } else if( log2TbHeight < 2 ){    log2SbH = log2TbHeight    log2SbW = 4 − log2SbH   }  }  numSbCoeff= 1 << ( log2SbW + log2SbH )  lastScanPos = numSbCoeff  lastSubBlock =(1 << ( log2TbWidth + log2TbHeight − (log2SbW + log2SbH ) ) ) − 1  do {  if( lastScanPos = = 0 ) {    lastScanPos = numSbCoeff    lastSubBlock−−   }   lastScanPos− −   xS = DiagScanOrder[ log2TbWidth − log2SbW ][log2TbHeight − log2SbH ]        [ lastSubBlock ][ 0 ]   yS =DiagScanOrder[ log2TbWidth − log2SbW ][ log2TbHeight − log2SbH ]       [ lastSubBlock ] [ l ]   xC = (xS << log2SbW ) + DiagScanOrder[log2SbW ][ log2SbH ][ lastScanPos ][ 0 ]   yC = ( yS << log2SbH ) +DiagScanOrder[ log2SbW ][ log2SbH ][ lastScanPos ][ 1 ]  } while( ( xC!= LastSignificantCoeffX ) | | (yC != LastSignificantCoeffY ) )  QState= 0  for( i = lastSubBlock; i >= 0; i− − ) {   startQStateSb = QState  xS = DiagScanOrder[ log2TbWidth − log2SbW ][ log2TbHeight − log2SbH ]       [ i ][ 0 ]   yS = DiagScanOrder[ log2TbWidth − log2SbW ][log2TbHeight − log2SbH ]        [ i ][ 1 ]   inferSbDcSigCoeffFlag = 0  if( ( i < lastSubBlock ) && ( i > 0 ) ) {    coded_sub_block_flag[ xS][ yS ] ae(v)    inferSbDcSigCoeffFlag = 1   }   firstSigScanPosSb =numSbCoeff   lastSigScanPosSb = −1   remBinsPass1 = ( ( log2SbW +log2SbH ) < 4 ? 8 : 32 )   firstPosMode0 = ( i = = lastSubBlock ?lastScanPos : numSbCoeff − 1 )   firstPosMode1 = −1   for( n =firstPosMode0; n >= 0 && remBinsPass1 >= 4; n− − ) {    xC = ( xS <<log2SbW ) + DiagScanOrder[ log2SbW ][ log2SbH ][ n ][ 0 ]    yC = ( yS<< log2SbH ) + DiagScanOrder[ log2SbW ][ log2SbH ][ n ][ 1 ]    if(coded_sub_block_flag[ xS ][ yS ] && (n > 0 | | !inferSbDcSigCoeffFlag )&&     ( xC != LastSignificantCoeffX | | yC != Last SignificantCoeffY )) {     sig_coeff_flag[ xC ][ yC ] ae(v)     remBinsPass1− −     if(sig_coeff_flag[ xC ][ yC ] )      inferSbDcSigCoeffFlag = 0     }    if( sig_coeff_flag[ xC ][ yC ]) {      abs_level_gtx_flag[ n ][ 0 ]ae(v)      remBinsPass1− −      if( abs_level_gtx_flag[ n ][ 0 ] ) {      par_level_flag[ n ] ae(v)       remBinsPass1− −      abs_level_gtx_flag[ n ][ 1 ] ae(v)       remBinsPass1− −      }     if( lastSigScanPosSb = = −1 )       lastSigScanPosSb = n     firstSigScanPosSb = n     }     AbsLevelPass1[ xC ][ yC ] =sig_coeff_flag[ xC ][ yC ] + par_level_flag[ n ] +      abs_level_gtx_flag[ n ][ 0 ] + 2 * abs_level_gtx_flag[ n ][ 1 ]    if( dep_quant_enabled_flag )      QState = QStateTransTable[ QState][ AbsLevelPass1 [ xC ][ yC ] & 1 ]     if( remBinsPass1 < 4 )     firstPosModel = n − 1   }   for( n = numSbCoeff − 1; n >=firstPosModel; n− − ) {    xC = (xS << log2SbW) + DiagScanOrder[ log2SbW][ log2SbH ][ n ][ 0 ]    yC = ( yS << log2SbH ) + DiagScanOrder[log2SbW ][ log2SbH ][ n ][ 1 ]    if( abs_level_gtx_flag[ n ][ 1 ])    abs_remainder[ n ] ae(v)    AbsLevel[ xC ][ yC ] = AbsLevelPass1[ xC][ yC ] +2 * abs_remainder[ n ]   }   for( n = firstPosModel; n >= 0; n−− ) {    xC = ( xS << log2SbW ) + DiagScanOrder[ log2SbW ][ log2SbH ][ n][ 0 ]    yC = ( yS << log2SbH ) + DiagScanOrder[ log2SbW ][ log2SbH ][n ][ 1 ]    dec_abs_level[ n ] ae(v)    if(AbsLevel[ xC ][ yC ] > 0 )    firstSigScanPosSb = n    if( dep_quant_enabled_flag)     QState =QStateTransTable[ QState ][ AbsLevel xC ][ yC ] & 1 ]   }   if(dep_quant_enabled_flag | | !sign_data_hiding_enabled_flag )   signHidden = 0   Else    signHidden = ( lastSigScanPosSb −firstSigScanPosSb > 3 ? 1 : 0 )   for( n = numSbCoeff − 1; n >= 0; n− −) {    xC = ( xS << log2SbW ) + DiagScanOrder[ log2SbW ][ log2SbH ][ n][ 0 ]    yC = ( yS << log2SbH ) + DiagScanOrder[ log2SbW ][ log2SbH ][n ][ 1 ]    if( ( AbsLevel[ xC ][ yC ] > 0 ) &&     (!signHidden (n !=firstSigScanPosSb ) ) )     coeff_sign_flag[ n ] ae(v)   }   if(dep_quant_enabled_flag) {    QState = startQStateSb    for( n =numSbCoeff − 1; n >= 0; n− − ) {     xC = (xS << log2SbW) +DiagScanOrder[ log2SbW ][ log2SbH ][ n ][ 0 ]     yC = ( yS << log2SbH) + DiagScanOrder[ log2SbW ][ log2SbH ][ n ][ 1 ]     if( AbsLevel[ xC][ yC ] > 0 )      TransCoeffLevel[ x0 ][ y0 ][ cIdx ][ xC ][ yC ] =      ( 2 * AbsLevel[ xC ][ yC ] − ( QState > 1 ? 1 : 0 ) ) *       ( 1− 2 * coeff_sign_flag[ n ] )     QState = QStateTransTable[ QState ][par_level_flag[ n ] ]   } else {    sum AbsLevel = 0    for( n =numSbCoeff − 1; n >= 0; n− − ) {     xC = ( xS << log2SbW ) +DiagScanOrder[ log2SbW ][ log2SbH ][ n ][ 0 ]     yC = ( yS << log2SbH) + DiagScanOrder[ log2SbW ][ log2SbH ][ n ][ 1 ]     if( AbsLevel[ xC][ yC ] > 0 ) {      TransCoeffLevel [ x0 ][ y0 ][ cIdx ][ xC ][ yC ] =       AbsLevel[ xC ][ yC ] * ( 1 − 2 * coeff_sign_flag[ n ] )      if(signHidden ) {       sumAbsLevel += AbsLevel[ xC ][ yC ]       if( ( n == firstSigScanPosSb ) && ( sumAbsLevel % 2 ) = = 1 ) )       TransCoeffLevel [ x0 ][ y0 ][ cIdx ][ xC ][ yC ] =        −TransCoeffLevel[ x0 ][ y0 ][ cIdx ][ xC ][ yC ]      }     }   }   }  } }

When the number of context models increases, the hardware and softwarecomplexity also increases. Therefore, it is desired to reduce the numberof context models without sacrificing coding efficiency. Particularly,it is desired to reduce the number of context models for the coding fortransform coefficient significance since it is more than 21% of the 424context models in standardized context modeling schemes in VVC Draft 5.

The embodiments of the present disclosure may be used separately orcombined in any order. Further, each of the methods, encoder and decoderaccording to the embodiments of the present disclosure may beimplemented by processing circuitry (e.g., one or more processors or oneor more integrated circuits). In one example, the one or more processorsexecute a program that is stored in a non-transitory computer-readablemedium. According to embodiments of the present disclosure, the termblock may be interpreted as a prediction block, a coding block, or acoding unit (i.e., CU).

According to some embodiments, a region is defined as a set of connectedtransform coefficient positions. For example, a region is a set of atransform coefficient positions (x, y) such that d₀≤x+y<d₁ for somenon-negative integer d₀ and d₁ called position thresholds. Embodimentsof the present disclosure can be applied to entropy coding techniques ofa transform coefficient significant flag (sig_coeff_flag) with thefollowing parameters:

-   -   (i) N is the number of context models per region. In one example        implementation, N is equal to 4. In another example        implementation, N is equal to 5.    -   (ii) d_(0Y) and d_(1Y) are the diagonal position thresholds for        Luma regions. In one example implementation, d_(0Y) is 2 and        d_(1Y) is 5.    -   (iii) d_(0C) is a diagonal position threshold for Chroma        regions. In one example implementation, doc is 2.    -   (iv) f(x) is a monotonic non-decreasing function which maps from        the set of non-negative integer to the set of non-negative        integer.    -   (v) When N is 5, an implementation of the function f(x) is        defined as        f(x)=x−(x>>2)    -   (vi) When N is 4, an implementation of the function f(x) is        defined as        f(x)=(x+1)>>1

According to some embodiments, when coding sig_coeff_flag[x][y] of thecurrent coefficient, the context model index is selected depending on avalue of sumAbs1 and a diagonal position d. More specifically, as shownin FIG. 14 , for a Luma component, the context model index is determinedin some embodiments according to:offset=min(f(sumAbs1),N−1)  Eq. (10):base=3*N*max(0,state−1)+(d<d0_(Y)?2*N:(d<d1_(Y) ?N:0))  Eq. (11):ctxSig=base+offset  Eq. (12):

For a Chroma component, the context model index is determined accordingto:offset=min(f(sumAbs1),N−1)  Eq. (13):base=2*N*max(0,state−1)+(d<d0_(C) ?N: 0)  Eq. (14):ctxSig=base+offset  Eq. (15):

where state specifies the scalar quantizer used if the dependentquantization is enabled and state is derived using a state transitionprocess. If dependent quantization is not enabled, in some examples thestate is equal to 0. Furthermore, in some embodiments, as shown in FIG.15 , when N is 4 or 5, the function min(f(sumAbs1), N−1) can also beimplemented for lower hardware complexity as f(min(sumAbs1, 5)).

Standardized context modeling schemes in VVC Draft 5 have 90 contextmodels for coding the significance of transform coefficients. In theembodiments of the present disclosure, when N is equal to 5, the numberof context model is reduced from 90 to 75, and when N is equal to 4, thenumber of context model is reduced from 90 to 60.

According, to some embodiments, the monotonic non-decreasing functionf(x) of non-negative integer x may be defined as:Σ_(i=0) ^(M) a _(i)×((x+b _(i))>>i),  Eq. (16):

where

${\sum_{i = 0}^{M}\frac{a_{i}}{2^{i}}} \geq 0$and, b_(i) is an integer value. Furthermore, a_(i) can be 0, 1 or −1 toreduce computation.

According to some embodiments, the context region depends on thediagonal position d, so that the number of context models per region maydepend on the diagonal position d to further reduce the number ofcontexts. For example, the number of context models per region with(d<d_(0Y)), (d_(0Y)<d<d_(1Y)) and (d_(1Y)<d<d_(2Y)) is N₁, N₂ and N₃,respectively. Particularly, the number of context models may vary basedon the value of d. In this case, the context model index may bedetermined according to:g ₁(x)=min(f ₁(x),N ₁−1)  Eq. (17):g ₂(x)=min(f ₂(x),N ₂−1)  Eq. (18):g ₃(x)=min(f ₃(x),N ₃−1)  Eq. (19):ctxSig=(N ₁ +N ₂ +N ₃)*max(0,state−1)+(d<d _(0Y)?(N ₂ +N ₃)+g₁(sumAbs1):(d<d _(1Y) ?N ₃ +g ₂(sumAbs1): g ₃(sumAbs1))),  Eq. (20):

where f₁(x), f₂(x) and f₃(x) are monotonic non-decreasing functions ofnon-negative integer x. Example values of N₁, N₂ and N₃ can be integervalues from 1 to 16. The embodiments including Eqs. (17)-(20) providemore flexibility by reducing the number of contexts with the samebitrate.

An alternative embodiment of the present disclosure can be applied toentropy coding techniques of a transform coefficient significant flagwith the following parameters:

-   -   (i) N is the number of context models per region. In this        implementation N is equal to 4.    -   (ii) d_(0Y) is the diagonal position threshold for Luma regions.        In this implementation, d_(0Y) is 5.    -   (iii) d_(0C) is the diagonal position threshold for Chroma        regions. In this implementation, d_(0C) is 2.    -   (iv) When N is 4, the function f(x) of non-negative integer x is        defined as        f(x)=(x+1)>>1

According to some embodiments, when coding sig_coeff_flag[x][y] of thecurrent coefficient, the context model index is selected depending onsumAbs1 and diagonal position d, where for a Luma component, the contextmodel index is determined according to:offset=min(f(sumAbs1),N−1)  Eq. (21):base=2*N*max(0,state−1)+(d<d _(0Y) ?N: 0)  Eq. (22):ctxSig=base+offset  Eq. (23):

For a Chroma component, the context model index is determined accordingto:offset=min(f(sumAbs1),N−1)  Eq. (24):base=2*N*max(0,state−1)+(d<d _(0C) ?N: 0)  Eq. (25):ctxSig=base+offset  Eq. (26):

where state specifies the scalar quantizer used if the dependentquantization is enabled and state is derived using a state transitionprocess. Otherwise, dependent quantization is not enabled, state isequal to 0.

In some embodiments, the function min(f(sumAbs1), N−1) can also beimplemented for lower hardware complexity as f(min(sumAbs1, 5)).

Standardized context model schemes in VVC Draft 5 have 90 context modelsfor coding the significance of transform coefficients. In the previouslydisclosed alternative embodiment (i.e., Eqs. (21)-(26)), when N equalsto 4, the number of context models is reduced from 90 to 48.

FIG. 16 illustrates an embodiment of a process performed by a decodersuch as video decoder (710). The process may start at step (S1600) wherea coded video bitstream including a current picture and at least onesyntax element that corresponds to transform coefficients of a transformblock in the current picture. As an example, the at least one syntax maybe sig_coeff_flag. The process proceeds to step (S1602) where an offsetvalue is determined based on an output of a monotonic non-decreasingfunction f(x) performed on a sum(x) of a group of partiallyreconstructed transform coefficients. The process proceeds to step(S1604) where a context model index is determined based on a sum of thedetermined offset value and a base value. As an example, the contextmodel index may be determined in accordance with the process illustratedin one of FIGS. 14 and 15 or the above disclosed alternative embodiment(i.e., Eqs. (21)-(26)). The process proceeds to step (S1606) where forthe at least one syntax of a current transform coefficient, a contextmodel from a plurality of context models based on the determined contextmodel index is selected.

FIG. 17 illustrates an embodiment of a process performed by a decodersuch as video decoder (710). The process may start at step (S1700) wherea coded video bitstream including a current picture and at least onesyntax element that corresponds to transform coefficients of a transformblock in the current picture. As an example, the at least one syntax maybe sig_coeff_flag. The process proceeds to step (S1702) where, for eachcontext model region from a plurality of context model regions, anoutput of a monotonic non-decreasing function performed on a sum(x) of agroup of partially reconstructed transform coefficients and a number ofcontext models associated with a respective context model region. Forexample, functions g₁(x)=min(f₁(x), N₁−1), g₂(x)=min(f₂(x), N₂−1), andg₃(x)=min(f₃(x), N₃−1) disclosed above may be used for a respectivecontext model region, where the number of context models per region(i.e., N₁, N₂, N₃) varies based on a distance of a current coefficientfrom a top left corner the transform block. The process proceeds to step(S1704) where a context model index is determined based on the output ofthe monotonic non-decreasing function of each context model region. Theprocess proceeds to step (S1706) where for the at least one syntax of acurrent transform coefficient, a context model from a plurality ofcontext models based on the determined context model index is selected.

The techniques described above, can be implemented as computer softwareusing computer-readable instructions and physically stored in one ormore computer-readable media. For example, FIG. 18 shows a computersystem (1800) suitable for implementing certain embodiments of thedisclosed subject matter.

The computer software can be coded using any suitable machine code orcomputer language, that may be subject to assembly, compilation,linking, or like mechanisms to create code comprising instructions thatcan be executed directly, or through interpretation, micro-codeexecution, and the like, by one or more computer central processingunits (CPUs), Graphics Processing Units (GPUs), and the like.

The instructions can be executed on various types of computers orcomponents thereof, including, for example, personal computers, tabletcomputers, servers, smartphones, gaming devices, internet of thingsdevices, and the like.

The components shown in FIG. 18 for computer system (1800) are exemplaryin nature and are not intended to suggest any limitation as to the scopeof use or functionality of the computer software implementingembodiments of the present disclosure. Neither should the configurationof components be interpreted as having any dependency or requirementrelating to any one or combination of components illustrated in theexemplary embodiment of a computer system (1800).

Computer system (1800) may include certain human interface inputdevices. Such a human interface input device may be responsive to inputby one or more human users through, for example, tactile input (such as:keystrokes, swipes, data glove movements), audio input (such as: voice,clapping), visual input (such as: gestures), olfactory input (notdepicted). The human interface devices can also be used to capturecertain media not necessarily directly related to conscious input by ahuman, such as audio (such as: speech, music, ambient sound), images(such as: scanned images, photographic images obtain from a still imagecamera), video (such as two-dimensional video, three-dimensional videoincluding stereoscopic video).

Input human interface devices may include one or more of (only one ofeach depicted): keyboard (1801), mouse (1802), trackpad (1803), touchscreen (1810), data-glove (not shown), joystick (1805), microphone(1806), scanner (1807), camera (1808).

Computer system (1800) may also include certain human interface outputdevices. Such human interface output devices may be stimulating thesenses of one or more human users through, for example, tactile output,sound, light, and smell/taste. Such human interface output devices mayinclude tactile output devices (for example tactile feedback by thetouch-screen (1810), data-glove (not shown), or joystick (1805), butthere can also be tactile feedback devices that do not serve as inputdevices), audio output devices (such as: speakers (1809), headphones(not depicted)), visual output devices (such as screens (1810) toinclude CRT screens, LCD screens, plasma screens, OLED screens, eachwith or without touch-screen input capability, each with or withouttactile feedback capability—some of which may be capable to output twodimensional visual output or more than three dimensional output throughmeans such as stereographic output; virtual-reality glasses (notdepicted), holographic displays and smoke tanks (not depicted)), andprinters (not depicted).

Computer system (1800) can also include human accessible storage devicesand their associated media such as optical media including CD/DVD ROM/RW(1820) with CD/DVD or the like media (1821), thumb-drive (1822),removable hard drive or solid state drive (1823), legacy magnetic mediasuch as tape and floppy disc (not depicted), specialized ROM/ASIC/PLDbased devices such as security dongles (not depicted), and the like.

Those skilled in the art should also understand that term “computerreadable media” as used in connection with the presently disclosedsubject matter does not encompass transmission media, carrier waves, orother transitory signals.

Computer system (1800) can also include an interface to one or morecommunication networks. Networks can for example be wireless, wireline,optical. Networks can further be local, wide-area, metropolitan,vehicular and industrial, real-time, delay-tolerant, and so on. Examplesof networks include local area networks such as Ethernet, wireless LANs,cellular networks to include GSM, 3G, 4G, 5G, LTE and the like, TVwireline or wireless wide area digital networks to include cable TV,satellite TV, and terrestrial broadcast TV, vehicular and industrial toinclude CANBus, and so forth. Certain networks commonly require externalnetwork interface adapters that attached to certain general purpose dataports or peripheral buses (1849) (such as, for example USB ports of thecomputer system (1800)); others are commonly integrated into the core ofthe computer system (1800) by attachment to a system bus as describedbelow (for example Ethernet interface into a PC computer system orcellular network interface into a smartphone computer system). Using anyof these networks, computer system (1800) can communicate with otherentities. Such communication can be uni-directional, receive only (forexample, broadcast TV), uni-directional send-only (for example CANbus tocertain CANbus devices), or bi-directional, for example to othercomputer systems using local or wide area digital networks. Certainprotocols and protocol stacks can be used on each of those networks andnetwork interfaces as described above.

Aforementioned human interface devices, human-accessible storagedevices, and network interfaces can be attached to a core (1840) of thecomputer system (1800).

The core (1840) can include one or more Central Processing Units (CPU)(1841), Graphics Processing Units (GPU) (1842), specialized programmableprocessing units in the form of Field Programmable Gate Areas (FPGA)(1843), hardware accelerators for certain tasks (1844), and so forth.These devices, along with Read-only memory (ROM) (1845), Random-accessmemory (1846), internal mass storage such as internal non-useraccessible hard drives, SSDs, and the like (1847), may be connectedthrough a system bus (1848). In some computer systems, the system bus(1848) can be accessible in the form of one or more physical plugs toenable extensions by additional CPUs, GPU, and the like. The peripheraldevices can be attached either directly to the core's system bus (1848),or through a peripheral bus (1849). Architectures for a peripheral businclude PCI, USB, and the like.

CPUs (1841), GPUs (1842), FPGAs (1843), and accelerators (1844) canexecute certain instructions that, in combination, can make up theaforementioned computer code. That computer code can be stored in ROM(1845) or RAM (1846). Transitional data can also be stored in RAM(1846), whereas permanent data can be stored for example, in theinternal mass storage (1847). Fast storage and retrieve to any of thememory devices can be enabled through the use of cache memory, that canbe closely associated with one or more CPU (1841), GPU (1842), massstorage (1847), ROM (1845), RAM (1846), and the like.

The computer readable media can have computer code thereon forperforming various computer-implemented operations. The media andcomputer code can be those specially designed and constructed for thepurposes of the present disclosure, or they can be of the kind wellknown and available to those having skill in the computer software arts.

As an example and not by way of limitation, the computer system havingarchitecture (1800), and specifically the core (1840) can providefunctionality as a result of processor(s) (including CPUs, GPUs, FPGA,accelerators, and the like) executing software embodied in one or moretangible, computer-readable media. Such computer-readable media can bemedia associated with user-accessible mass storage as introduced above,as well as certain storage of the core (1840) that are of non-transitorynature, such as core-internal mass storage (1847) or ROM (1845). Thesoftware implementing various embodiments of the present disclosure canbe stored in such devices and executed by core (1840). Acomputer-readable medium can include one or more memory devices orchips, according to particular needs. The software can cause the core(1840) and specifically the processors therein (including CPU, GPU,FPGA, and the like) to execute particular processes or particular partsof particular processes described herein, including defining datastructures stored in RAM (1846) and modifying such data structuresaccording to the processes defined by the software. In addition or as analternative, the computer system can provide functionality as a resultof logic hardwired or otherwise embodied in a circuit (for example:accelerator (1844)), which can operate in place of or together withsoftware to execute particular processes or particular parts ofparticular processes described herein. Reference to software canencompass logic, and vice versa, where appropriate. Reference to acomputer-readable media can encompass a circuit (such as an integratedcircuit (IC)) storing software for execution, a circuit embodying logicfor execution, or both, where appropriate. The present disclosureencompasses any suitable combination of hardware and software.

APPENDIX A: ACRONYMS

-   -   JEM: joint exploration model    -   VVC: versatile video coding    -   BMS: benchmark set    -   MV: Motion Vector    -   HEVC: High Efficiency Video Coding    -   SEI: Supplementary Enhancement Information    -   VUI: Video Usability Information    -   GOPs: Groups of Pictures    -   TUs: Transform Units,    -   PUs: Prediction Units    -   CTUs: Coding Tree Units    -   CTBs: Coding Tree Blocks    -   PBs: Prediction Blocks    -   HRD: Hypothetical Reference Decoder    -   SNR: Signal Noise Ratio    -   CPUs: Central Processing Units    -   GPUs: Graphics Processing Units    -   CRT: Cathode Ray Tube    -   LCD: Liquid-Crystal Display    -   OLED: Organic Light-Emitting Diode    -   CD: Compact Disc    -   DVD: Digital Video Disc    -   ROM: Read-Only Memory    -   RAM: Random Access Memory    -   ASIC: Application-Specific Integrated Circuit    -   PLD: Programmable Logic Device    -   LAN: Local Area Network    -   GSM: Global System for Mobile communications    -   LTE: Long-Term Evolution    -   CANBus: Controller Area Network Bus    -   USB: Universal Serial Bus    -   PCI: Peripheral Component Interconnect    -   FPGA: Field Programmable Gate Areas    -   SSD: solid-state drive    -   IC: Integrated Circuit    -   CU: Coding Unit

While this disclosure has described several exemplary embodiments, thereare alterations, permutations, and various substitute equivalents, whichfall within the scope of the disclosure. It will thus be appreciatedthat those skilled in the art will be able to devise numerous systemsand methods which, although not explicitly shown or described herein,embody the principles of the disclosure and are thus within the spiritand scope thereof.

(1) A method of video decoding performed in a video decoder, the methodincluding receiving a coded video bitstream including a current pictureand at least one syntax element that corresponds to transformcoefficients of a transform block in the current picture; determining anoffset value based on an output of a monotonic non-decreasing f(x)function performed on a sum (x) of a group of partially reconstructedtransform coefficients; determining a context model index based on a sumof the determined offset value and a base value; and selecting, for theat least one syntax of a current transform coefficient, a context modelfrom a plurality of context models based on the determined context modelindex.

(2) The method of feature (1), in which one of the base value and offsetvalue is determined based on a number of context models included in theplurality of context models.

(3) The method according to feature (2), the method further including:determining whether dependent quantization is enabled for the currentcoefficient, and in response to the determination that dependentquantization is enabled for the current coefficient, the base value isbased on a state of a quantizer.

(4) The method according to feature (3), in which the currentcoefficient is located in a luma region, and the base value is based ona comparison of a distance of the current coefficient from a top leftcorner the transform block with a first diagonal position threshold.

(5) The method according to feature (4), in which the base value isfurther based on a comparison of the distance with a second diagonalposition threshold.

(6) The method according to feature (3), in which the currentcoefficient is located in a chroma region, and the base value is basedon a comparison of a distance of the current coefficient from a top leftcorner the transform block with a first diagonal position threshold.

(7) The method according to any one of features (1)-(6), in which themonotonic non-decreasing function is defined as x−(x>>2).

(8) The method according to any one of features (1)-(6), in which themonotonic non-decreasing function is defined as (x+1)>>1.

(9) The method according to any one of features (1)-(8), in which thecurrent coefficient and the group of partially reconstructed transformcoefficients form a template that constitutes a contiguous set oftransform coefficients.

(10) The method according to any one of features (1)-(9), in which theat least one syntax element is a transform coefficient significant flag(sig_coeff_flag).

(11) The method according to any one of features (1)-(10), in which thebit stream includes a plurality of syntax elements that include the atleast one syntax element, and in which the sum (x) of the group ofpartially reconstructed transform coefficients is based on one or moresyntax elements from the plurality of syntax elements.

(12) A method of video decoding performed in a video decoder, the methodincluding: receiving a coded video bitstream including a current pictureand at least one syntax element that corresponds to transformcoefficients of a transform block in the current picture; determining,for each context model region from a plurality of context model regions,an output of a monotonic non-decreasing function performed on a sum (x)of a group of partially reconstructed transform coefficients and anumber of context models associated with a respective context modelregion; determining a context model index based on the output of themonotonic non-decreasing function of each context model region; andselecting, for the at least one syntax of a current transformcoefficient, a context model from a plurality of context models based onthe determined context model index.

(13) The method according to feature (12), in which the determining ofthe context model index is further based on a comparison of a distanceof the current coefficient from a top left corner the transform blockwith a first diagonal position threshold and a second diagonal positionthreshold.

(14) The method according to feature (12), in which the determining ofthe context model index is further based on a comparison of a distanceof the current coefficient from a top left corner the transform blockwith a first diagonal position.

(15) A video decoder for video decoding, including processing circuitryconfigured to: receive a coded video bitstream including a currentpicture and at least one syntax element that corresponds to transformcoefficients of a transform block in the current picture, determine anoffset value based on an output of a monotonic non-decreasing f(x)function performed on a sum (x) of a group of partially reconstructedtransform coefficients, determine a context model index based on a sumof the determined offset value and a base value, and select, for the atleast one syntax of a current transform coefficient, a context modelfrom a plurality of context models based on the determined context modelindex.

(16) The video decoder according to feature (15), in which one of thebase value and offset value is determined based on a number of contextmodels included in the plurality of context models.

(17) The video decoder according to feature (16), in which theprocessing circuitry is further configured to: determine whetherdependent quantization is enabled for the current coefficient, and inresponse to the determination that dependent quantization is enabled forthe current coefficient, the base value is based on a state of aquantizer.

(18) The video decoder according to feature (17), in which the currentcoefficient is located in a luma region, and the base value is based ona comparison of a distance of the current coefficient from a top leftcorner the transform block with a first diagonal position threshold.

(19) The video decoder according to feature (18), in which the basevalue is further based on a comparison of the distance with a seconddiagonal position threshold.

(20) A video decoder apparatus for video decoding including processingcircuitry configured to: receive a coded video bitstream including acurrent picture and at least one syntax element that corresponds totransform coefficients of a transform block in the current picture,determine, for each context model region from a plurality of contextmodel regions, an output of a monotonic non-decreasing functionperformed on a sum (x) of a group of partially reconstructed transformcoefficients and a number of context models associated with a respectivecontext model region, determine a context model index based on theoutput of the monotonic non-decreasing function of each context modelregion, and select, for the at least one syntax of a current transformcoefficient, a context model from a plurality of context models based onthe determined context model index.

What is claimed is:
 1. A method of video decoding in a decoder, themethod comprising: receiving a coded video bitstream, the coded videobitstream including coded syntax elements that are associated withtransform coefficients of a transform block in a current picture;determining, for a scan position in the transform block, an offset valuebased on a template magnitude for a template of the scan position, thetemplate of the scan position including a group of partiallyreconstructed transform coefficients, the offset value being constrainedbased on a first number of context models for each frequency region, thefirst number being less than a second number of potential values for thetemplate magnitude; determining, for the scan position, a base valuebased on the first number and the scan position; determining a contextmodel index based on a sum of the offset value and the base value;selecting a context model from a plurality of context models based onthe context model index; determining a value of a syntax element at thescan position based on the context model; and determining a transformcoefficient at the scan position based on the value of the syntaxelement.
 2. The method according to claim 1, wherein the determining theoffset value further comprises: determining the offset value based on anoutput of a monotonically non-decreasing function performed on thetemplate magnitude.
 3. The method according to claim 2, wherein themonotonically non-decreasing function is defined as x−(x>>2).
 4. Themethod according to claim 2, wherein the monotonically non-decreasingfunction is defined as (x+1)>>1.
 5. The method according to claim 1,further comprising: determining whether dependent quantization isenabled for the transform coefficient; and in response to the dependentquantization being enabled for the transform coefficient, determiningthe base value based on a state of a quantizer.
 6. The method accordingto claim 5, wherein the transform coefficient is located in a lumaregion, and the base value is based on a comparison of a distance of thescan position of the transform coefficient to a top left corner of thetransform block with a first diagonal position threshold.
 7. The methodaccording to claim 6, wherein the base value is further based on acomparison of the distance with a second diagonal position threshold. 8.The method according to claim 5, wherein the transform coefficient islocated in a chroma region, and the base value is based on a comparisonof a distance of the scan position of the transform coefficient to a topleft corner of the transform block with a first diagonal positionthreshold.
 9. The method according to claim 1, wherein the template ofthe scan position includes the group of partially reconstructedtransform coefficients that are neighboring the scan position andconstitute a contiguous set of transform coefficients with the transformcoefficient at the scan position.
 10. The method according to claim 1,wherein the syntax element is a transform coefficient significant flag.11. An apparatus, comprising processing circuitry configured to: receivea coded video bitstream, the coded video bitstream including codedsyntax elements that are associated with transform coefficients of atransform block in a current picture; determine, for a scan position inthe transform block, an offset value based on a template magnitude for atemplate of the scan position, the template of the scan positionincluding a group of partially reconstructed transform coefficients, theoffset value being constrained based on a first number of context modelsfor each frequency region, the first number being less than a secondnumber of potential values for the template magnitude; determine, forthe scan position, a base value based on the first number and the scanposition; determine a context model index based on a sum of the offsetvalue and the base value; select a context model from a plurality ofcontext models based on the context model index; determine a value of asyntax element at the scan position based on the context model; anddetermine a transform coefficient at the scan position based on thevalue of the syntax element.
 12. The apparatus according to claim 11,wherein the processing circuitry is configured to: determine the offsetvalue based on an output of a monotonically non-decreasing functionperformed on the template magnitude.
 13. The apparatus according toclaim 12, wherein the monotonically non-decreasing function is definedas x−(x>>2).
 14. The apparatus according to claim 12, wherein themonotonically non-decreasing function is defined as (x+1)>>1.
 15. Theapparatus according to claim 11, wherein the processing circuitry isconfigured to: determine whether dependent quantization is enabled forthe transform coefficient; and in response to the dependent quantizationbeing enabled for the transform coefficient, determine the base valuebased on a state of a quantizer.
 16. The apparatus according to claim15, wherein the scan position is in a luma region, and the base value isbased on a comparison of a distance of the scan position of thetransform coefficient to a top left corner of the transform block with afirst diagonal position threshold.
 17. The apparatus according to claim16, wherein the base value is further based on a comparison of thedistance with a second diagonal position threshold.
 18. The apparatusaccording to claim 15, wherein the transform coefficient is in a chromaregion, and the base value is based on a comparison of a distance of thescan position of the transform coefficient to a top left corner of thetransform block with a first diagonal position threshold.
 19. Theapparatus according to claim 11, wherein the template of the scanposition includes the group of partially reconstructed transformcoefficients that are neighboring the scan position and constitute acontiguous set of transform coefficients with the transform coefficientat the scan position.
 20. The apparatus according to claim 11, whereinthe syntax element is a transform coefficient significant flag(sig_coeff_flag).